Εκ μέρους του καθηγ. κ. Ι. Πήτα σας ενημερώνουμε για το παρακάτω:
Dear Computer Vision/Machine Learning/Autonomous Systems students, engineers, scientists and enthusiasts,
due to numerous requests worldwide, asynchronous access is now offered to Computer Vision and Machine Learning (CVML) Web lecture material:
- a) lecture pdf/ppt, b) lecture video, c) lecture understanding questionnaire d) lecture satisfaction questionnaire.
This allows individual study at own pace.
The following lectures are already in the repository:
- Introduction to Autonomous Systems
- Introduction to Computer vision
- Image acquisition, camera geometry
- Stereo and Multiview imaging
Two more lectures are added each week, the next to come being:
- Structure from Motion
- 2D convolution and correlation algorithms
Registration can be done using the link: http://icarus.csd.auth.gr/cvml-web-lecture-series/
No new registration is needed for old registrants, just an email to Ioanna Koroni <email@example.com> or Orestis Sarakatsanos firstname.lastname@example.org.
All other provisions for CVML Web lectures (certificate of participation etc) apply.
These lectures are part of a 14 lecture CVML web course ‘Computer vision and machine learning for autonomous systems’ (April-June 2020):
Introduction to autonomous systems (delivered 25th April 2020)
Introduction to computer vision (delivered 25th April 2020)
Image acquisition, camera geometry (delivered 2nd May 2020)
Stereo and Multiview imaging (delivered 2nd May 2020)
Structure from Motion
2D convolution and correlation algorithms
Introduction to Machine Learning
Introduction to neural networks, Perceptron, backpropagation
Deep neural networks, Convolutional NNs
Deep learning for object/target detection
Localization and mapping
Fast convolution algorithms. CVML programming tools.
Lecturer: Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and PhD degree in Electrical Engineering, both from the Aristotle University of Thessaloniki, Greece. Since 1994, he has been a Professor at the Department of Informatics of the same University. He served as a Visiting Professor at several Universities.
His current interests are in the areas of image/video processing, machine learning, computer vision, intelligent digital media, human centered interfaces, affective computing, 3D imaging and biomedical imaging. He has published over 1138 papers, contributed in 50 books in his areas of interest and edited or (co-)authored another 11 books. He has also been member of the program committee of many scientific conferences and workshops. In the past he served as Associate Editor or co-Editor of 9 international journals and General or Technical Chair of 4 international conferences. He participated in 70 R&D projects, primarily funded by the European Union and is/was principal investigator/researcher in 42 such projects. He has 30000+ citations to his work and h-index 81+ (Google Scholar).
Prof. Pitas lead the big European H2020 R&D project MULTIDRONE: https://multidrone.eu/ and is principal investigator (AUTH) in H2020 projects Aerial Core and AI4Media. He is chair of the Autonomous Systems initiative https://ieeeasi.signalprocessingsociety.org/.
Prof. I. Pitas: https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el
AIIA Lab www.aiia.csd.auth.gr
Lectures will consist primarily of live lecture streaming and PPT slides. Attendees (registrants) need no special computer equipment for attending the lecture. They will receive the lecture PDF before each lecture and will have the ability to ask questions real-time. Audience should have basic University-level undergraduate knowledge of any science or engineering department (calculus, probabilities, programming, that are typical e.g., in any ECE, CS, EE undergraduate program). More advanced knowledge (signals and systems, optimization theory, machine learning) is very helpful but nor required.
Prof. Ioannis Pitas
Director of AIIA Lab, Aristotle University of Thessaloniki, Greece
Post scriptum: To stay current on CVMl matters, you may want to register to the CVML email list, following instructions in https://lists.auth.gr/sympa/info/cvml